The goal of this research is to develop an innovative prototypical medical device treatment system capable of detecting and visualizing three dimensional shape and tip position of a biopsy needle during Magnetic Resonance Imaging (MRI) or other image-assisted interventional radiological procedures. This work will be done in collaboration with interventional radiologist Professor Bruce Daniel's group at the Stanford Medical School, Professor Mark Cutkosky's group at the Stanford Center for Design Research (CDR) and HeartVista, for clinical imaging platform software integration. In addition, our potential clients and strategic partners Civco, Northern Digital (NDI) and Hologic will provide guidance and other in-kind contributions to help us accelerate the development of the technology and assist in the FDA approval process. Minimally invasive procedures, including biopsies of hard tumors, rely on advances in miniaturized tools and robotic assistance to reduce trauma to patients and speed healing times. Present tools lack the real-time position awareness that surgeons use to an advantage in open surgery. The liver was chosen as an organ subject due to the high need to reduce positional error and minimize multiple needle passes, thus improving clinical outcomes, especially in patients susceptible to excessive bleeding due to underlying liver disease. The ability to guide biopsy of abnormalities seen on cross-sectional imaging studies is well recognized in tissue diagnosis, and MRI provides a number of significant advantages over other imaging modalities. This is all the more true with the advent of new long lived contrasting agents that can only work in tandem with MRI. The principal specific aim is to demonstrate that an innovative needle design deploying fiber optic sensors for guidance (in 3D) and force-feedback can be used in tandem with MRI to enhance the conduct of liver biopsies. Our clinical and industry partners advise us of a growing interest towards interventional procedures, such as biopsies, ablations, and cryosurgeries performed under continual MR scanning. During Phase I, sensors multiplexed along optical fibers were embedded into 18 gauge biopsy needles and used to provide real-time visualization of the entire needle bend shape, including the needle tip position. This was augmented by force sensing design features integrated into the same needle tip. During Phase II, the work will be extended to demonstrate reliable shape sensing through more detailed in vitro work followed by selected in vivo experiments in animal models. In addition, Phase II will integrate force sensing capability with fiber Bragg gratings (FBG) and IFOS' interrogator technology to provide force feedback. Work will culminate in a prototype MRI-compatible, physician-controlled needle system for image-guided liver procedures. The technology can be adapted to other imaging modalities, including ultrasound (US) and computer tomography (CT). The proposed work will advance the field of smart needle development for robotic surgery with potentially broad-based spin-off applications in oncology, biological imaging and bioengineering.